Por favor, use este identificador para citar o enlazar a este item: http://hdl.handle.net/10261/150282
COMPARTIR / EXPORTAR:
logo share SHARE logo core CORE BASE
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE

Invitar a revisión por pares abierta
Título

Characterizing the environments of supernovae with MUSE

AutorGalbany, Lluís CSIC ORCID ; Pérez Jiménez, Enrique CSIC ORCID ; Moral, V.
Palabras claveSupernovae: general
Techniques: spectroscopic
Methods: statistical
H II regions
Galaxies: general
Fecha de publicación2016
EditorOxford University Press
CitaciónMonthly Notices of the Royal Astronomical Society 455: 4087- 4099 (2016)
ResumenWe present a statistical analysis of the environments of 11 supernovae (SNe) which occurred in six nearby galaxies (z ≲ 0.016). All galaxies were observed with MUSE, the high spatial resolution integral-field spectrograph mounted to the 8 m VLT UT4. These data enable us to map the full spatial extent of host galaxies up to ~3 effective radii. In this way, not only can one characterize the specific host environment of each SN, one can compare their properties with stellar populations within the full range of other environments within the host. We present a method that consists of selecting all HII regions found within host galaxies from 2D extinction-corrected Hα emission maps. These regions are then characterized in terms of their Hα equivalent widths, star formation rates and oxygen abundances. Identifying HII regions spatially coincident with SN explosion sites, we are thus able to determine where within the distributions of host galaxy e.g. metallicities and ages each SN is found, thus providing new constraints on SN progenitor properties. This initial pilot study using MUSE opens the way for a revolution in SN environment studies where we are now able to study multiple environment SN progenitor dependencies using a single instrument and single pointing. © 2015 The Authors.
URIhttp://hdl.handle.net/10261/150282
DOI10.1093/mnras/stv2620
Identificadoresdoi: 10.1093/mnras/stv2620
issn: 1365-2966
Aparece en las colecciones: (IAA) Artículos




Ficheros en este ítem:
Fichero Descripción Tamaño Formato
IAA_2016_MNRASstv2620.pdf8,41 MBAdobe PDFVista previa
Visualizar/Abrir
Mostrar el registro completo

CORE Recommender

SCOPUSTM   
Citations

93
checked on 16-abr-2024

WEB OF SCIENCETM
Citations

87
checked on 23-feb-2024

Page view(s)

289
checked on 19-abr-2024

Download(s)

202
checked on 19-abr-2024

Google ScholarTM

Check

Altmetric

Altmetric


NOTA: Los ítems de Digital.CSIC están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.